Andreessen Horowitz’s Olivia Moore on the Current State and Future of Consumer AI

A New Report Highlights Gaps and Opportunities in Consumer AI

Olivia Moore, a partner at Andreessen Horowitz, released a report on Monday that ranks the top 100 consumer AI applications. ChatGPT remains the dominant player by a wide margin, while smaller tools such as Suno and ElevenLabs are demonstrating real staying power. Perhaps most striking, the report identifies half a dozen consumer categories that appear untouched by AI, pointing to significant white space for future entrants.

Revenue Challenges and the Search for New Monetization Models

This interview has been edited for length and clarity.

It’s an interesting moment for a report about consumer AI, since we’ve seen OpenAI pivot back to enterprise this year. It’s inspired a lot of pessimism about the overall revenue picture for consumer AI, including from me. But I take it you’re more optimistic?

Moore responded that OpenAI’s shift toward enterprise is more an expansion than a pivot, noting that the company continues to launch many consumer offerings. She explained that most AI revenue so far has come from subscriptions and token usage, which are heavily concentrated on enterprise and prosumer users.

How can consumer AI products change that revenue problem? The State of Markets report reminded us that just 2.2% of U.S. households are paying for AI. Do we need that number to rise before the market becomes attractive?

Moore said she does not necessarily want to see the user base grow. Instead, she prefers a model where consumers are monetized without requiring them to pay subscription fees out of pocket. She argued that many users would rather access tools for free with ads and optionally subscribe to remove ads, a pattern common among high‑income users with corporate cards.

The other challenge is the marginal cost of AI services, which is still a lot higher than classic internet services like Facebook or Google Search. Do you see a lot of these services finding ways to keep those costs down, whether it’s open-source or other lightweight models?

Moore observed that costs are improving. ChatGPT now offers a Go plan priced at $8 per month, likely running on cheaper models. She noted that frontier intelligence is not required for every task, and that more consumer companies are building on open‑source models. However, current revenue is driven by technical automation users who need advanced models. As more developers target consumers where the model is not the product, lower‑cost models will become more common.

It’s unusual to talk about technical automation in a consumer service, which feels like another unique feature of AI. Are we starting to blur the lines between consumer and enterprise?

Moore referenced her earlier article “The Great Expansion,” which described how pre‑AI consumer companies such as Canva took six or seven years to add enterprise plans. In contrast, newer firms like Gamma, ElevenLabs, and Cursor have moved from consumer origins to majority‑enterprise businesses within 18 months. She argued that much of what is called consumer AI is actually prosumer AI, reflected in revenue patterns that cluster around three categories: product‑building apps (Lovable, Replit, Fal), product marketing tools (Higgsfield, HeyGen), and general work‑management solutions (Manus, Fireflies AI, Granola). These are initially paid for by consumers but do not fit the traditional consumer model.

Moore also pointed out the absence of entrants in the top 100 list for whitespace categories such as social apps, dating apps, marketplaces, retail, travel, finance, and health. She expects these areas to see activity over the next six months.

Outlook: Early Days and Untapped Potential

Moore concluded that the consumer AI market is still in its early stages. While the current landscape is dominated by a few big names and a handful of niche successes, the lack of AI presence in many everyday categories suggests substantial room for innovation. If developers can find sustainable revenue models beyond subscriptions and API charges, and if costs continue to decline through open‑source and lighter models, the next wave of consumer AI could look very different from today’s offerings.